The current research aims to diagnose the role of social responsibility as a contributing factor in enhancing the quality of services provided by the public sector in Iraq, where the research sought to demonstrate the relationship and impact of social responsibility dimensions (economic, legal, moral, and human) on the sector Services related to the electric field in Nineveh governorate because of its importance and its direct relationship with the citizen especially after the end of military operations in the destruction of the electricity sector by a large percentage in the city of Mosul. Nineveh Electricity Distribution Directorate / Center was chosen as a research community including (administrators and staff) of the research

Purpose: The research aims to diagnose the current availability of knowledge workers characteristics and the role of these characteristics in knowledge acquision in the city of Sulaimaniya Directorate of Electricity, and to identify the differences between personal and occupational characteristics of a sample of research and its impact on the availability of such properties.

Design/methodology/approach :to achieve the objectives of the research questionnaire was developed especially for it and then distributed to a sample of engineers and technicians working in the Directorate of Electricity city of Sulaimaniya, where the sample of the research (52) respondents.

Findings:  the most important conclusions reached

Abstract
        The research has discussed the public relations as dependent variable of its branch dimensions( confidence , commitment, control and satisfaction ) and the governmental service quality as independent variable of its branch dimensions (response, dependency, emphasis, tangibility and sympathy), and the research problem has represented by weakness of service quality presented to the customers dealing with company, which is observed via  field co-existence of the researcher, where he observe that the quality presented in the company services, are inappropriate with the customers expectations level, also there is weakness of attention and recognition by the

Nowadays, cloud computing has attracted the attention of large companies due to its high potential, flexibility, and profitability in providing multi-sources of hardware and software to serve the connected users. Given the scale of modern data centers and the dynamic nature of their resource provisioning, we need effective scheduling techniques to manage these resources while satisfying both the cloud providers and cloud users goals. Task scheduling in cloud computing is considered as NP-hard problem which cannot be easily solved by classical optimization methods. Thus, both heuristic and meta-heuristic techniques have been utilized to provide optimal or near-optimal solutions within an acceptable time frame for such problems. In th

Speech enhancement aims to improve speech quality and intelligibility in noisy environments and is important in applications such as hearing aids, mobile communications and automatic speech recognition (ASR). This paper shows a structured review of speech enhancement techniques, classified depending on the channel configuration and signal processing framework. Both traditional and modern approaches are discussed, including classical signal processing methods, machine learning techniques, and recent deep learning-based models. Furthermore, common noise types, widely used speech datasets, and standard evaluation metrics for evaluating speech quality and intelligibility are reviewed. Key challenges such as non-stationary noise, data li

Portland cement concrete is the most commonly used construction material in the world for decades. However, the searches in concrete technology are remaining growing to meet particular properties related to its strength, durability, and sustainability issue. Thus, several types of concrete have been developed to enhance concrete performance. Most of the modern concrete types have to contain supplementary cementitious materials (SCMs) as a partial replacement of cement. These materials are either by-products of waste such as fly ash, slag, rice husk ash, and silica fume or from a geological resource like natural pozzolans and metakaolin (MK). Ideally, the utilization of SCMs will enhance the concrete performance, minimize

Translating news between Arabic and English is more complex than it may initially appear. The process is far more than the process of finding the same words, as it usually touches upon the structural differences, cultural allusions, and in most situations, the ideological pressure. This critical literature review is based on a narrative synthesis of 18 peer-reviewed studies published from 2023 to 2026 and explores the interaction of these factors in real journalistic practice. An even closer examination of the literature indicates that there are three common points of challenge. Firstly, structural and lexical differences between Arabic and English can be observed that have to be constantly adjusted to. Second, cultural and religious allusi

Large language models (LLMs) are a rapidly evolving class of artificial intelligence with significant potential in clinical healthcare. Despite accelerating adoption, rigorous systematic evidence on clinical utility, patient safety, and implementation feasibility remains fragmented. To systematically review LLM applications across clinical domains, evaluate performance with appropriate contextual caveats, characterize implementation barriers, and identify ethical and regulatory considerations. Scientific databases were searched from January 2020 to January 2025. Studies evaluating transformer-based LLMs (≥10M parameters) in clinical settings were eligible. Data were independently double-extracted; quality was assessed using QUADAS-2, RE-A